Massively parallel Bayesian inference for transient gravitational-wave astronomy

Understanding the properties of transient gravitational waves and their sources is of broad interest in physics and astronomy. Bayesian inference is the standard framework for astro-physical measurement in transient gravitational-wave astronomy. Usually, stochastic sampling algorithms are used to estimate posterior probability distributions over the parameter spaces of models describing experimental data. The most physically accurate models typically come with a large computational overhead which can render data analysis extremely time consuming, or possibly even prohibitive. In some cases highly specialized optimizations can mitigate these issues, though they can be difficult to implement, as well as to generalize to arbitrary models of the data. Here, we propose an accurate, flexible and scalable method for astro-physical inference: parallelized nested sampling. The reduction in the wall-time of inference scales almost linearly with the number of parallel processes running on a high-performance computing cluster. By utilizing a pool of several hundreds or thousands of CPUs in a high-performance cluster, the large wall times of many astrophysical inferences can be alleviated while simultaneously ensuring that any gravitational-wave signal model can be used "out of the box", i.e., without additional optimization or approximation. Our method will be useful to both the LIGO-Virgo-KAGRA collaborations and the wider scientific community performing astrophysical analyses on gravitational waves. An implementation is available in the open source gravitational-wave inference library $\texttt{pBilby}$ (parallel $\texttt{bilby}$).Comment: 9 pages, 2 figures, 1 tabl

Augmented balancing weights as linear regression

We provide a novel characterization of augmented balancing weights, also known as Automatic Debiased Machine Learning (AutoDML). These estimators combine outcome modeling with balancing weights, which estimate inverse propensity score weights directly. When the outcome and weighting models are both linear in some (possibly infinite) basis, we show that the augmented estimator is equivalent to a single linear model with coefficients that combine the original outcome model coefficients and OLS; in many settings, the augmented estimator collapses to OLS alone. We then extend these results to specific choices of outcome and weighting models. We first show that the combined estimator that uses (kernel) ridge regression for both outcome and weighting models is equivalent to a single, undersmoothed (kernel) ridge regression; this also holds when considering asymptotic rates. When the weighting model is instead lasso regression, we give closed-form expressions for special cases and demonstrate a ``double selection'' property. Finally, we generalize these results to linear estimands via the Riesz representer. Our framework ``opens the black box'' on these increasingly popular estimators and provides important insights into estimation choices for augmented balancing weights

Massively parallel Bayesian inference for transient gravitational-wave astronomy

Understanding the properties of transient gravitational waves (GWs) and their sources is of broad interest in physics and astronomy. Bayesian inference is the standard framework for astrophysical measurement in transient GW astronomy. Usually, stochastic sampling algorithms are used to estimate posterior probability distributions over the parameter spaces of models describing experimental data. The most physically accurate models typically come with a large computational overhead which can render data analsis extremely time consuming, or possibly even prohibitive. In some cases highly specialized optimizations can mitigate these issues, though they can be difficult to implement, as well as to generalize to arbitrary models of the data. Here, we investigate an accurate, flexible, and scalable method for astrophysical inference: parallelized nested sampling. The reduction in the wall-time of inference scales almost linearly with the number of parallel processes running on a high-performance computing cluster. By utilizing a pool of several hundreds or thousands of CPUs in a high-performance cluster, the large wall times of many astrophysical inferences can be alleviated while simultaneously ensuring that any GW signal model can be used ‘out of the box’, i.e. without additional optimization or approximation. Our method will be useful to both the LIGO-Virgo-KAGRA collaborations and the wider scientific community performing astrophysical analyses on GWs. An implementation is available in the open source gravitational-wave inference library pBilby (parallel bilby)

Planetary Spectrum Generator: an accurate online radiative transfer suite for atmospheres, comets, small bodies and exoplanets

We have developed an online radiative-transfer suite (https://psg.gsfc.nasa.gov) applicable to a broad range of planetary objects (e.g., planets, moons, comets, asteroids, TNOs, KBOs, exoplanets). The Planetary Spectrum Generator (PSG) can synthesize planetary spectra (atmospheres and surfaces) for a broad range of wavelengths (UV/Vis/near-IR/IR/far-IR/THz/sub-mm/Radio) from any observatory (e.g., JWST, ALMA, Keck, SOFIA), any orbiter (e.g., ExoMars, Juno), or any lander (e.g., MSL). This is achieved by combining several state-of-the-art radiative transfer models, spectroscopic databases and planetary databases (i.e., climatological and orbital). PSG has a 3D (three-dimensional) orbital calculator for most bodies in the solar system, and all confirmed exoplanets, while the radiative-transfer models can ingest billions of spectral signatures for hundreds of species from several spectroscopic repositories. It integrates the latest radiative-transfer and scattering methods in order to compute high resolution spectra via line-by-line calculations, and utilizes the efficient correlated-k method at moderate resolutions, while for computing cometary spectra, PSG handles non-LTE and LTE excitation processes. PSG includes a realistic noise calculator that integrates several telescope / instrument configurations (e.g., interferometry, coronagraphs) and detector technologies (e.g., CCD, heterodyne detectors, bolometers). Such an integration of advanced spectroscopic methods into an online tool can greatly serve the planetary community, ultimately enabling the retrieval of planetary parameters from remote sensing data, efficient mission planning strategies, interpretation of current and future planetary data, calibration of spectroscopic data, and development of new instrument/spacecraft concepts.Comment: Journal of Quantitative Spectroscopy and Radiative Transfer, submitte

Long-term clinical outcome of peripheral nerve stimulation for chronic headache and complication prevention

Background: Subcutaneous peripheral nerve stimulation (PNS) has emerged as a useful tool in the treatment of intractable headaches. However, complications such as skin erosion, infection and lead migration have adversely affected clinical outcome, and occasionally led to treatment cessation. Objectives: Here we report the results of peripheral nerve stimulator implantation performed on 24 patients with various chronic headaches at our center over a period of 9 years. We describe the complications of the procedure and their prevention with a modified surgical technique. Patients and Methods:We searched our database for patients with chronic refractory headacheswhohad undergone PNS. Patients were assessed before being considered for PNS, and their pain characteristics were reviewed. Following a successful trial, patients were implanted with a permanent peripheral nerve stimulator. Selection of target nerves was based on headache diagnosis and head pain characteristics. Patients were followed for an average of 4.9 years. Headache characteristics before and after treatment were compared. Results: Twenty four patients were included in the study. All patients reported on improvement in head pain intensity, duration and frequency three months after permanent device implantationMeantotal pain index (TPI) decreased significantly, from 516±131 before the procedure to 74.8±61.6 at the last follow up (P \u3c 0.00001). There were no acute post-operative infections. Three patients had their stimulator removed. The self-rated treatment satisfaction was excellent in 54% of the patients, very good or good in 42%, and fair in 4%. Conclusions: Our results support the use of PNS insomepatients with refractory chronic headaches. Appropriate surgical planning and technique are important to achieve good clinical outcome and to minimize complications. © 2016, Iranian Society of Regional Anesthesia and Pain Medicine (ISRAPM). All rights reserved

Baryogenesis and gravity waves from a UV-completed electroweak phase transition

We study gravity wave production and baryogenesis at the electroweak phase transition in a real singlet scalar extension of the Standard Model, including vectorlike top partners, to generate the CP violation needed for electroweak baryogenesis (EWBG). The singlet makes the phase transition strongly first order through its coupling to the Higgs boson, and it spontaneously breaks CP invariance through a dimension-five contribution to the top quark mass term, generated by integrating out the heavy top quark partners. We improve on previous studies by incorporating updated transport equations, compatible with large bubble wall velocities. The wall speed and thickness are computed directly from the microphysical parameters rather than treating them as free parameters, allowing for a first-principles computation of the baryon asymmetry. The size of the CP-violating dimension-five operator needed for EWBG is constrained by collider, electroweak precision, and renormalization group running constraints. We identify regions of parameter space that can produce the observed baryon asymmetry or observable gravitational wave (GW) signals. Contrary to standard lore, we find that for strong deflagrations, the efficiencies of large baryon asymmetry production and strong GW signals can be positively correlated. However, we find the overall likelihood of observably large GW signals to be smaller than estimated in previous studies. In particular, only detonation-type transitions are predicted to produce observably large gravitational waves.Peer reviewe